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Werthmann, B.

Publications and source records attributed to Werthmann, B..

2 recordsLinked to original sources

Quantifying 35 transcripts in a single tube: Model-based calibration of the GeXP RT-PCR assay

Quantitative analysis of differential gene expression is of central importance in molecular life sciences. The Gene eXpression Profiling technology (GeXP) relies on multiplex RT-PCR and subsequent capillary electrophoretic separation of the amplification products and allows to quantify the transcripts of up to approximately 35 genes with a single reaction and one dye. Here, we provide a kinetic model of primer binding and PCR product formation as the rational basis for taking and evaluating calibration curves. With the help of a purposeful designed data processing workflow supported by easy-to-use Perl scripts for calibration, data evaluation, and quality control, the calibration procedure and the model predictions were confirmed and the robustness and linearity of transcript quantification demonstrated for differentiating Physarum polycephalum plasmodial cells. We conclude that GeXP analysis is a robust, sensitive, and useful method when the transcripts of tens to few hundred genes are to be precisely quantified in a high number of samples.

systems biology

Developmental switching in Physarum polycephalum: Petri net analysis of single cell trajectories of gene expression indicates responsiveness and genetic plasticity of the Waddington quasipotential landscape

The developmental switch to sporulation in Physarum polycephalum is a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.

systems biology